A mental health profile has only recently emerged of portions of American Indian (AI) populations. Documenting the prevalence of diagnosed conditions, however, is only the first step: Subsyndromal or partial manifestations of disorder likely hold important implications for progression, service use, and prevention. Additionally, measures of distress or impairment associated with mental illness, independent of diagnosis, have been shown to capture different dimensions of mental health, making their role in the formulation of DSM-V a topic of heated debate. Finally, "cultural idioms" of emotional problems in AI populations are likely to provide a cultural map of mental illness to complement and elaborate mental illness captured by other measures. As important to delineating the dimensions of mental illness, is understanding the context in which they arise. Cultural beliefs, family processes, and community conditions -- net of those of the individual -- are instrumental in our understanding of mental illness and subsequent service use, particularly in AI populations where kinship and community life is integral to daily life. Yet, to date, rigorous analyses delineating family and community influences have been absent. [unreadable] [unreadable] Innovative research in other populations has demonstrated the importance of community context in mental illness and service use. These efforts have focused mainly on urban areas or large national populations. Recently, data have become available for a multilevel investigation among rural AIs. Data from the American Indian Service Utilization, Psychiatric Epidemiology, and Risk/Protective Factors Project (AI- SUPERPFP), specifically designed to investigate mental illness and services in these populations, and now appended with geocoded community and geospatial information, make these data ideal for addressing the complex and multilayered factors associated with AI psychiatric disorders and service use. This proposal responds to Program Announcement (PA-07-103; Research on Rural Mental Health and Drug Abuse Disorders). It will address the following aims: [1] Determine the demography of mental illness, including psychiatric disorders (full and subsyndromal), cultural idioms, distress, and impairment within and across two AI tribes; [2] place mental illness in community and family context through the development of multilevel models; and [3] extend the multilevel models to determine the family, community, and geospatial context of service use, including both biomedical and traditional modalities. [unreadable] [unreadable] [unreadable]